JPH1080560A - Game house management system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To recognize the popularity of a game machine with high accuracy by counting not only a player who is playing a game on the game machine but also those around the specific game machine who are not playing the game. SOLUTION: Entering/leaving person counting devices 1, 1 count the numbers of players going in and out of a passage between two islands and outputs the counts to a control device 2. The counting part of the control device 2 for the number of game machines in service calculates the number of game machines now in service by inputting from the game machines in operation the data showing that the machines are being operated. A counting part 4 for the number of people calculates the number of players in the passage who are not playing games from the numbers of entering and leaving persons input from the entering/leaving person counting devices 1, 1 and from the count of the number of game machines in service, and stores the result in a count storing part 6. An analyzing part 7 reads the stored counts when necessary to originate analytical data showing the popularity of the game machines.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system for managing information relating to amusement machines in a playground such as a pachinko hall.

[0002]

2. Description of the Related Art In recent years, a large number of models have been introduced into pachinko halls, and models are frequently replaced and layouts are frequently changed. In such a hall, each amusement machine is connected to a management host computer, and while the amusement program is running,
Data relating to the insertion and withdrawal of game media (hereinafter referred to as "game data") is transmitted to the host computer as appropriate.

The host computer uses the game data transmitted from each game machine to create analysis data indicating the operating rate of each model, the time used per player, the number of game media used, and the like. The analysis data is output in a form such as a display or a printout as appropriate, and is used by a business operator to recognize the degree of popularity of each model.

[0004]

In the above-described method, the popularity is simply recognized based on the usage status from the game machine, and the customer or game development waiting for the game machine being used to open is determined. I can't figure out how many customers to visit.
For this reason, in the case of a particularly popular model, it is impossible to determine how many customers are actually interested in the model and how the popularity of the model will change in the future.
It is difficult to adequately meet the demands of gamers.

[0005] The present invention has been made in view of the above-mentioned problems, and the popularity of a specific game machine is analyzed by using the number of players in an area including the specific game machine, thereby obtaining a game. It is an object of the present invention to provide a playground management system capable of recognizing the popularity of a game machine with high accuracy.

[0006]

According to a first aspect of the present invention, there is provided a playground management system comprising: a counting means for counting the number of gamers who enter and exit an area including a specific game machine in a playground; Calculation means for calculating the number of gamers in the area using numerical values, and analysis means for creating analysis data related to the degree of popularity of the specific game machine using calculation results by the calculation means. ing.

According to a second aspect of the present invention, the calculating means receives a signal indicating whether or not a game is being played from the specific game machine and recognizes a use state of the game machine in the area. Thereafter, based on the recognition result and the count value of the counting means, the number of game players who are not playing a game in the area is calculated.

According to a third aspect of the present invention, the counting means associates a plurality of image pickup means for picking up an image of the vicinity of the entrance of the area with images obtained by simultaneous image pickup by the respective image pickup means. It includes a recognition unit for extracting three-dimensional data indicating a customer, and a recognition unit for tracking a temporal transition of the extraction result by the extraction unit and recognizing a gamer who enters and exits the area.

According to a fourth aspect of the present invention, the counting means extracts an image of the vicinity of the entrance of the area, and extracts a feature indicating a gamer from an image obtained by the imaging means. It includes an extracting means and a recognizing means for recognizing a gamer who enters and exits the area by tracking a temporal transition of an extraction result by the extracting means.

[0010] In the playground management system according to a fifth aspect, the counting means measures height data near the entrance and exit of the area, and extracts gamers near the entrance and exit based on the measurement result by the measuring means. It includes an extracting means and a recognizing means for recognizing a gamer who enters and exits the area by tracking a temporal transition of an extraction result by the extracting means.

In the amusement arcade management system according to a sixth aspect of the present invention, the analyzing means tracks the calculation result by the calculating means in a time-series manner and creates analysis data indicating a change in the degree of popularity of the specific amusement machine. It is composed of

According to a seventh aspect of the present invention, the analysis means inputs a predetermined fluctuation factor together with the calculation result by the staying person number calculation means, and indicates a relationship between the input fluctuation factor and the degree of popularity. It is configured to create analytical data.

[0013]

According to the first aspect of the present invention, after the number of players entering and exiting an area including a specific amusement machine is counted, the number of players in the area is calculated using the counted value, thereby providing a game. Analytical data that accurately reflects the popularity of the machine is created.

According to the second aspect of the present invention, a signal indicating whether or not a game is being played is input from a specific game machine to recognize the use status of the game machine, and the recognition result and the count value of the counting means are used as a result. Based on this, it is possible to accurately calculate the number of gamers who are not playing a game in the area.

According to the third aspect of the present invention, a plurality of imaging means are used to simultaneously image the vicinity of the entrance and exit of the area, and then the three-dimensional data representing the gamer is extracted by associating each image with each other. Since the time-dependent transition is used to recognize a player entering or leaving the area, even if the player is approaching, it is possible to separately recognize each player.

According to the fourth aspect of the present invention, a feature indicating a gamer is extracted from an image obtained by imaging the vicinity of the entrance of the area, and the user enters and exits the area using the temporal transition of the extraction result. Players are recognized.

According to the fifth aspect of the present invention, after height data in the vicinity of the entrance and exit of the area is measured, a gamer is extracted from the measurement result, and the user enters and exits the area using the temporal transition of the extraction result. Recognition of the game player to be performed is performed.

According to the sixth aspect of the present invention, the transition of the popularity of the amusement machine is analyzed based on the temporal change of the calculation result of the number of players in the area.

According to the seventh aspect of the present invention, the analysis data in which the popularity of the amusement machine is associated with a predetermined variation factor is created.

[0020]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A preferred configuration example of a playground management system according to the present invention will be described with reference to FIG. 2 to 14 show a first embodiment of the counting means according to claim 1, and FIGS. 15 and 16 show a second embodiment of the counting means.
17 and 18, a third embodiment of the counting means is shown in FIG.
9 shows a fourth embodiment of the counting means. Further, with reference to FIG. 20, an example of analysis data relating to the popularity of amusement machines by the playground management system of FIG. 1 will be described.

[0021]

FIG. 1 shows a configuration example of a management system in a pachinko hall according to an embodiment of the present invention. This management system is for analyzing the popularity of pachinko machines constituting each of two facing islands in a hall, and includes two entrance / exit measurement devices 1, 1 and each entrance / exit measurement device. 1,
And a control device 2 for inputting the measurement value of 1 and analyzing the popularity.

Each of the entry / exit measurement devices 1, 1 is for measuring a player entering and exiting a passage PT (shown in FIG. 2) between predetermined islands 3, 3 in the hall. It is located near the entrance at the end and counts the number of people entering the aisle (hereinafter referred to as “number of visitors”) and the number of people who go outside the aisle (hereinafter “number of exits”) Then, the measurement result is output to the control device 2.

The control device 2 is constituted by a personal computer or the like, and includes, as main components, a people counting section 4, a used number measuring section 5, a count value storage section 6, an analyzing section 7, etc. The peripheral configuration includes an input unit 8 for inputting data such as fluctuation factors to be described later, and an output unit 9 for displaying or printing out the analysis result.

The number-of-uses counting section 5 receives the above-mentioned game data from each of the operating game machines and counts the number of the game machines running the game. Is input to The people counting unit 4 calculates the number of players in the current passage PT by subtracting the number of visitors and the number of exits input from the entering / leaving person measuring device 1, 1 and further calculating the number of players in the passage PT. By subtracting the measured value of the used number, the number of players who are not playing the game in the passage PT is calculated.

The count value storage unit 6 stores the count values obtained by the number counting unit 4 in time series. The stored data is read out by the analysis unit 7 as appropriate, and analysis data relating to the popularity of the amusement machines forming each of the islands 3 is created.

The entrance / exit measurement device 1 performs a measurement process using an image picked up by a television camera.
As shown in FIG. 2, regions R, R of a predetermined size that cover the entrances at both ends of the passage PT are set as the measurement regions of the entrance / exit measurement devices 1.

As shown in FIG. 3, each entry / exit measurement device 1 includes two imaging units 10a and 10b, an image memory 11, a feature point processing unit 12, a separation processing unit 13, a tracking processing unit 14, a discrimination processing unit. The components such as 15, memory 16 and output unit 17 are connected via a bus 18.

The image pickup units 10a and 10b are respectively provided with television cameras 20a and 20b (hereinafter simply referred to as "cameras 20a and 2b").
0b ") and A / D conversion circuits 21a and 21b, and performs an imaging operation at the same timing based on a synchronization signal c provided from a timing control unit (not shown).

The cameras 20a and 20b have substantially the same focal length. As shown in FIG.
9 is accommodated and arranged in a state where the optical axis is substantially parallel. At the time of installation, each of the cameras 20a and 20b is arranged in a horizontal direction at a position above the passage PT, directly downward or with a certain depression angle, and images one of the measurement regions R. . At this time, the image signals g1 and g2 from the respective cameras are converted into A / D conversion circuits 21a and 21b, respectively.
After that, it is stored in the image memory 11.

FIG. 5 shows the procedure for measuring the number of visitors by the above-mentioned person measuring apparatus 1, and the operation of each section will be described with reference to FIGS. I do. In the first step 1 (indicated by “ST1” in the figure),
One of the measurement regions R by the imaging units 10a and 10b
Is imaged, and the image data is taken into the image memory 11, the feature points on each image are extracted by the feature point processing unit 12, and the feature points are associated between the two images (step 2). .

As a method of extracting the feature points, for example,
A method of scanning an arbitrary local area on an image to extract edge constituent points, a method of extracting a pixel having a large change by subtracting a background image captured in advance without a player for each input image, A method of subtracting the input image taken in the previous stage from the input image of (1) to extract a pixel having a large change can be considered.

In order to associate feature points between the two images, one of the images is set as a reference image, and a predetermined image area centered on the feature points extracted on the reference image is extracted. Next, an image area having the image data having the highest similarity to the image data in this image area is searched on the other image, and the center point of the area is determined as the corresponding point of the feature point.

In this embodiment, the cameras 20a, 20a
20b are arranged side by side in the horizontal direction, so that when an object point P on an object is imaged, the object point P on each image is obtained.
The Y coordinates Y _L , Y _R of the image points P _L , P _R are substantially at the same position as shown in FIG.

Therefore, the feature processing unit 12 of this embodiment
Actually focuses on the y coordinate of the feature point on the reference image,
A feature point having the same y coordinate value as the noted y coordinate on the other image and a feature point located in the vicinity thereof are set as corresponding point candidates for the feature point. Further, for each of these candidate points, the feature processing unit 12 sets an image area centered on the point, and searches for an image area most similar to the image area on the reference image from these. As a result, the feature point in the image region having the highest similarity is recognized as corresponding to the feature point of the reference image, and an improvement in processing speed and a highly accurate association process can be realized.

When the association of the extracted feature points is completed, the separation processing unit 13 calculates the spatial coordinates of each feature point (step 3). The calculation processing of the spatial coordinates is performed by applying the two-dimensional coordinates of the associated feature points and the parameters of the camera to the principle of triangulation, and the separation processing unit 13 further calculates the spatial coordinates based on the calculation results.
Each feature point is grouped for each person, and each player is separated and recognized (step 4).

The specific procedure of the separation recognition process will be described below with reference to FIGS. First, of the feature points extracted in the measurement region R, the separation processing unit extracts only feature points having predetermined height data (here, 0.5 m) as candidate feature points indicating a human. I do.

FIG. 7 shows a specific example of this extraction result. The x-axis in the figure corresponds to the width direction of the passage PT similarly to the x-axis on the two-dimensional screen by the cameras 20a and 20b, and the z-axis is the depth direction of the measurement region R (that is, the length of the passage PT). Direction). Each filled rectangle is a feature point that satisfies the above condition, and its height data (y coordinate value) is 0.5 to 1.0 m, 1.0 to 1.5 m, 1.5
The range of m or more is identified by the type of paint. In this embodiment, all feature points of 1.5 m or more are extracted. However, an upper limit value may be set in the extraction range, and feature points having height data exceeding the upper limit value may be excluded. good.

When a person exists in the measurement area R,
As shown in FIG. 7, a plurality of feature points are gathered within a certain range, and the height data (corresponding to the head) of the feature point located at the center in the aggregate is the highest. The result of the extraction is obtained. Based on this principle, the separation processing unit 13 performs a clustering process on the extracted feature points to integrate the feature points in order, and for each generated cluster, the configuration of the height data satisfies the human condition. Recognize whether it is.

If feature points P1 and P2 as shown in FIG. 8 have been extracted, the distance L1 between these feature points P1 and P2 (obtained by equation (1)) or each feature point P
1, the distance L2 between the projection points of P2 on the xz plane ((2)
(Obtained by the equation) is equal to or smaller than a predetermined threshold value, these feature points P1 and P2 are determined to belong to the same cluster.

[0040]

(Equation 1)

[0041]

(Equation 2)

When the distance L2 is used, a value obtained by adding the height component of each feature point (the maximum value, the minimum value, or the average value of each y coordinate) to the distance L2 is used as a threshold value. You may make it compare with.

As shown in FIG. 9, four feature points Pa, P
When a feature point Px exists near a cluster consisting of b, Pc, and Pd, for example, the distance between the feature point Px and the point Pd closest to the feature point Px in the cluster or the feature point Px in the cluster By comparing the distance between the distant point Pa and the feature point Px with the threshold value, the feature point Px is calculated.
It is determined whether or not x is integrated into the cluster. Alternatively, the center of gravity of the cluster may be calculated based on the coordinates of each feature point in the cluster, and the determination may be performed using the distance between the center of gravity and the feature point Px.

When the integration process of each feature point is completed by the above method, the separation processing unit 13 selects a representative point from each cluster. As the representative point, various methods are conceivable, such as selecting a feature point corresponding to the head having the highest y-coordinate value, and calculating the center of gravity or the center point of the cluster to be a representative point.

The coordinates of the representative point selected in this way are recognized as a human extraction position and stored in the memory 16. The memory 16 stores an extraction position recognized for each image input.
Tracks the movement of the player in the measurement area R using the time series data of the extraction result (step 5).

FIG. 10 shows a specific example of the tracking process. FIG. 10 (1) shows the extraction result at a certain sampling time T1, and FIG. 10 (2) shows the extraction result at the next sampling time T + 1. .

At time T + 1, the tracking processing unit 14
Each extraction point (indicated by a circle in the figure) is associated with the closest point among the extraction points in the previous stage (indicated by a star in the figure) (the association result is indicated by an arrow in the figure), and further, these correspondences The distance of the assigned point is compared with the maximum distance that a human can move between the time T and the time T + 1. As a result, if the distance between the associated extraction points is within the maximum distance, these extraction points are recognized as indicating the same gamer. In this way, by associating the extraction points indicating the same gamer with each image input, data indicating the movement locus of the gamer in the measurement area (hereinafter referred to as “flow line data”) is created. Is done.

The above-mentioned tracking processing is terminated when the corresponding extraction point is no longer detected. Next, the discrimination processing section 18 performs the discrimination of the entering and leaving persons and the processing of measuring the number of entering and leaving persons. (Step 6).

FIG. 11 shows a specific example of the flow line data.
Here, in order to simplify the explanation, each flow line data K1,
K2 represents an image viewed from directly above the measurement region R. In the figure, L indicates a passing line corresponding to the entrance and exit of the passage PT, and by this passing line L, the measurement region R is divided into a region A on the outer portion of the passage and a region B in the passage. You.

The flow line data moving from the area A to the area B as indicated by K1 in the figure is determined as data indicating a visitor to the passage PT. Further, the flow line data moving from the area B to the area A as indicated by K2 is determined as data indicating the exiting person from the passage PT.

Next, a detailed procedure of the discrimination processing unit 15 corresponding to step 6 in FIG. 3 will be described with reference to FIG.
When the detection of the flow line data is completed, the determination processing unit 15
Gets the coordinates of the start and end points of the flow line data,
It is checked which of these areas A and B these points are in (steps 6-1 and 6-2). As a result, when it is determined that the start point and the end point are in different areas, the determination processing unit 15 recognizes that the gamer is passing through the passing line L, and furthermore, the end points are in the areas A and B. Is checked (step 6-3).

If the end point is in the area A, step 6
-3 is "YES", and the determination processing unit 15 determines that the flow line data indicates the exiting person from the passage PT, and adds "1" to the exiting number. On the other hand, if the end point is in the area B, step 6-3 becomes “NO”, and the discrimination processing unit 15 determines that the flow line data indicates a person entering the passage, and Is added by “1”.

The number of entrances and exits measured in this way is
The data is transmitted from the output unit to the control device 2 and is used for creating the analysis data related to the popularity.

According to the above-described entrance / exit measurement apparatus 1, recognition and tracking of a gamer in the measurement area are performed based on the spatial coordinates of the feature points extracted in the measurement area. Even if it moves, each person can be separated and identified, and a highly accurate measurement result can be obtained.

In the above embodiment, each of the measurement areas R, R
Although two cameras are provided every time, the present invention is not limited to this, and three or more cameras may be provided. FIG. 13 shows an example in which an imaging unit is configured by three cameras 20a, 20b, and 20c. In this case, an object is obtained by using one of three combinations of selecting any two of the three cameras. The space coordinates of the point P are calculated. As a result, FIG.
As shown in (2), for an object point P 'for which imaging by one of the cameras is impossible due to the presence of an obstacle, the spatial coordinates of the point P' can be calculated by the other two cameras.

As shown in FIG. 13, in the case of an object point P that can be imaged by any of the cameras 20a, 20b, and 20c, spatial coordinates are measured by three combinations of cameras, and these measured values are used. May be integrated to output the final measurement result. Also, for this object point P, the measured value of the spatial coordinates obtained by a combination of a certain camera is compared with the measured value of the spatial coordinates obtained by a combination of another camera, and the measured results of both are within a predetermined range. Only in certain cases, a highly reliable measurement value may be adopted. As described above, by using three or more cameras, a gamer in the measurement area R can be detected with higher accuracy.
The accuracy of the tracking processing and the measurement processing of the entrance and exit can be improved.

In addition, the imaging unit of the entrance / exit measurement device 1 is
It may be configured with a single camera, and a feature indicating a person may be extracted from an image from this camera, and the change over time may be tracked to count the number of visitors. As in the first embodiment, the feature extraction method is a method of extracting a pixel having a large change by subtracting a background image or an input image one step before from an input image, or a method of extracting edge constituent points on the input image. The extraction method and the like can be appropriately selected.

FIG. 15 shows a specific method for extracting features from an image obtained by the single camera. FIG. 15 (1)
This is a background image that captures a state in which there is no player in the measurement area R, and is an image PT showing the passage PT and each of the islands 3 and 3.
', 3', 3 'appear. FIG. 15 (2) shows an input image under measurement processing. For each pixel of the input image, the data of the corresponding pixel of the background image is subtracted to obtain a human image as shown in FIG. 15 (3). For example, features 30 and 31 indicating a moving object are extracted.

The above extraction result is compared with a previously stored human model image (shown in FIG. 15 (4)).
The extracted features are cut out for each size corresponding to the model image, and each player is separately recognized. In the case of the examples of FIGS. 15 (3) and (4), the feature 30 on the difference image is recognized as a feature for one player, and the feature 31 is recognized as a feature for two players.

The above recognition results are stored in a memory in a time series, and by tracking the transition of the recognition results,
Flow line data indicating the movement locus of each player is detected. FIGS. 16 (1) and (2) show an example of the above tracking processing.
FIG. 16A shows a feature extraction result at a certain sampling time T, and FIG.
1 shows the result of feature extraction.

At the time of the tracking process, based on the difference image at the time T, for each player recognized at this time,
An image region r1 including the feature is set, and the image data in the image region r1 is registered as a model image. Thereafter, on the difference image at time T + 1, the time T
A region r2 of a predetermined size is set as a search region at a position centered on the feature extraction position at the time point.

The size of the search area r2 is determined at the time T
Is determined in accordance with the maximum distance that a human can move from time T to time T + 1. In this search area r2, an image area r3 most similar to the model image is extracted, and the image data of the image area r3 is It is recognized as the same player image as the model image. In addition to this method,
For each of the separated features, a predetermined representative point such as the center point may be extracted, and the position of the extracted point may be tracked at each sampling time in the same manner as in FIG.

It is not always necessary to introduce an image processing method into the passing person counting apparatus, and it is possible to easily measure the number of people entering and exiting by using a transmission type sensor or a distance measuring sensor. FIG. 17 shows a specific example of the measurement processing by the transmission type sensor, and two sets of light receivers 32 are provided at both ends of the island 3, respectively. Island 3 opposite
A light projector (not shown) is provided at a position corresponding to each of the light receivers 32, 32.

The output signals from the light receivers 32, 32 are input to a counting device (not shown), and the on / off operations and the order of the light receivers 32, 32 determine the entrance / exit person and perform the counting process. Will be

FIGS. 18 and 19 show a specific example of the measurement processing by the distance measuring sensor. The vicinity of the ceiling of each entrance of the passage PT is set as the detection areas R1 and R1. In each of the detection areas R1 and R1, a plurality of distance measurement sensors 33 are provided.
Are arranged in two rows at equal distances in the width direction of the passage PT, and the distance from each sensor mounting position to an object directly below (the floor surface when there is no object) is measured. Will be

The output signal from each sensor 33 is input to a measurement processing device (not shown), and based on a change in the value measured by each sensor, the entry / exit person is determined and a counting process is performed. In the case of this embodiment, even when a plurality of gamers pass the doorway side by side, or when a visitor and an exited person pass each other at the doorway, each player can be separated and determined. A highly reliable measurement value can be obtained with a simple configuration.

Any of the above-described four embodiments may be used as the entrance / exit measurement device 1, and a device having a configuration according to the specifications and budget of the hall may be selected.

Next, the analysis processing by the analysis unit 7 of the control device 2 will be described. FIG. 20 shows an output example of the analysis data relating to the degree of popularity by the analysis unit 7. As for five models M1 to M5, each of the five models M1 to M5 has a game player who is not in a game in the path of the island where the models are deployed. Tabular data in which the numbers are summarized in units of 30 minutes are output.

The output format is not limited to the above format.
The number of waiters for each model during the week can be edited into a format that can be compared for each day of the week, and data can be created that associates the number of waiters with sales for each model. An application example of is considered.

Further, from the input unit 8, information such as weather information such as temperature and weather, local event information such as festivals, and event information relating to sales promotion in the hall is input, which is a factor for changing the number of visitors to the store. You may be comprised so that the analysis data which matched the factor and the popularity may be produced. In addition, a service such as issuing a numbered ticket may be implemented by quickly grasping a game player waiting for an open platform using the above configuration.

In the above-described embodiment, the number of game players who are not playing a game is calculated in a predetermined path between islands in a pachinko hall, and the popularity of the game machines forming the islands is analyzed based on the calculation result. However, the present invention is not limited to this, and can be applied to other playgrounds such as a game center. In this case, a predetermined area including a specific amusement machine is set as a measurement area, and the number of gamers who enter and exit this area is measured. Then, as described above, the number of gamers who are not playing in the area is calculated. By calculating, information on the popularity of the specific game machine is created.

[0072]

As described above, according to the present invention, after counting the number of players entering and exiting an area including a specific amusement machine in a playground, the number of players in the area is determined using the counted value. The calculation results are used to create analysis data on the popularity of a specific game machine, so that not only gamers playing but also games around the specific game machine are played. It is possible to easily and accurately recognize the popularity of amusement machines by grasping the amusement players.

According to the second aspect of the present invention, a signal indicating whether or not a game is being played is input from a specific game machine to recognize the use state of the game machine, and the recognition result and the count value of the counting means are used. The number of gamers who are not playing a game can be accurately calculated.

According to the third aspect of the present invention, a plurality of imaging means are used to simultaneously image the vicinity of the entrance and exit of the area, and then the three-dimensional data representing the gamer is extracted by associating each image with each other. Since the time-varying transition is used to recognize the gamers who enter and leave the area, each of the gamers is extracted with high accuracy, and the counting process can be performed with high accuracy.

According to the fourth aspect of the present invention, a feature indicating a gamer is extracted from an image obtained by imaging the vicinity of the entrance of the area, and the user enters and exits the area using the temporal transition of the extraction result. Since a gamer is recognized, a highly accurate counting process can be performed with a simpler configuration than the third aspect of the present invention.

According to the fifth aspect of the present invention, height data in the vicinity of the entrance of the area is measured, and the gamers are extracted from the measurement result. Can be separated and recognized, and a highly reliable count value can be obtained with a simple configuration.

According to the sixth aspect of the present invention, the transition of the popularity of the game machine is analyzed based on the temporal change of the calculation result of the number of players in the area. Can provide powerful analytical data for making decisions.

According to the seventh aspect of the present invention, since the analysis data in which the popularity of the amusement machine is associated with the predetermined variation factor is created, the variation factor such as the weather, the day of the week, various events, and the like can be obtained. You can recognize the relationship.

[Brief description of the drawings]

FIG. 1 is a block diagram showing one configuration example of a playground management system according to the present invention.

FIG. 2 is an explanatory diagram showing a measurement area of a passing person counting device.

FIG. 3 is a block diagram showing a detailed configuration of a passing person counting device.

FIG. 4 is an explanatory diagram showing an arrangement configuration of a camera.

FIG. 5 is a flowchart showing a procedure for counting visitors.

FIG. 6 is an explanatory diagram showing the correspondence between feature points between images.

FIG. 7 is an explanatory diagram showing a result of extracting three-dimensional coordinates of a feature point.

FIG. 8 is an explanatory diagram related to a clustering process.

FIG. 9 is an explanatory diagram related to a clustering process.

FIG. 10 is an explanatory diagram relating to tracking processing.

FIG. 11 is an explanatory diagram relating to an entry / exit discrimination process.

FIG. 12 is a flowchart illustrating a procedure for a process of determining and counting the number of visitors.

FIG. 13 is an explanatory diagram illustrating an example of a measurement process by three cameras.

FIG. 14 is an explanatory diagram illustrating an example of measurement processing by three cameras.

FIG. 15 is an explanatory diagram showing a feature extraction method in a case where measurement processing is performed by one camera.

FIG. 16 is an explanatory diagram showing a tracking processing method of a feature extraction result.

FIG. 17 is an explanatory diagram showing a mounting position of a sensor when a measurement process is performed using a transmission sensor.

FIG. 18 is an explanatory diagram showing a measurement area when performing a measurement process using a distance measurement sensor.

FIG. 19 is an explanatory diagram showing an example of the arrangement of distance measuring sensors.

FIG. 20 is an explanatory diagram showing an output example of analysis data.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Entering / exiting person measuring device 2 Control device 4 People counting part 5 Number of used parts measuring part 6 Count storage part 7 Analysis part 10a, 10b Imaging part 12 Feature processing part 13 Separation processing part 14 Tracking processing part 15 Judgment processing part

Claims (7)

[Claims] 1. A counting means for counting the number of gamers entering and leaving an area including a specific amusement machine in a playground; and using the count value of the counting means to determine the number of gamers in the area. A playground management system comprising: a calculating means for calculating; and an analyzing means for creating analysis data relating to the popularity of the specific amusement machine using a result of the calculation by the calculating means. 2. The calculation means receives a signal indicating whether or not a game is being played from the specific game machine to recognize the use state of the game machine in the area, and thereafter, the recognition result and the counting 2. The playground management system according to claim 1, wherein the number of game players who are not playing a game in the area is calculated based on the count value by the means. 3. The counting means extracts a plurality of three-dimensional data indicating a player by associating a plurality of imaging means for imaging the vicinity of the entrance of the area with images obtained by simultaneous imaging by the respective imaging means. 3. The playground management system according to claim 1, further comprising: a recognition unit for performing the search and a recognition unit for recognizing a gamer who enters and exits the area by tracking a temporal transition of an extraction result by the extraction unit. 4. The counting means includes: an image pickup means for picking up an image of the vicinity of the entrance of the area; an extraction means for extracting a feature indicating a player from an image obtained by the image pickup means; 2. The playground management system according to claim 1, further comprising a recognition unit that tracks a temporal transition of the extraction result and recognizes a gamer who enters and exits the area. 5. The counting means includes: measuring means for measuring height data near an entrance / exit of the area; extracting means for extracting a gamer near the entrance / exit based on a measurement result by the measuring means; 2. The playground management system according to claim 1, further comprising a recognition unit that tracks a temporal transition of the extraction result and recognizes a gamer who enters and exits the area. 6. The playground according to claim 1, wherein said analysis means creates analysis data indicating a change in popularity of said specific game machine by tracking a calculation result by said calculation means in time series. Management system. 7. The analysis means inputs a predetermined variation factor together with a calculation result by the staying person number calculation means, and creates analysis data indicating a relationship between the input variation factor and popularity. Playground management system described in.